Computer Sciences Commons^™

Unsupervised Machine Learning In Agent-Based Modeling, Luke D. Robinson

Celebration of Learning

Agent-based models (ABMs) are used by researchers in a variety of fields to model natural phenomena. In an ABM, a wide range of behaviors and outcomes can be observed based on the parameters of the model. In many cases, these behaviors can be categorized into discrete outcomes identifiable by human observers. Our goal was to use clustering algorithms to identify those outcomes from model output data. For this project, we used data from the NetLogo Wolf Sheep Predation model to explore and evaluate three clustering algorithms from Python's scikit-learn package. If this task can be completed reliably by a computer, …